• The KIPS Transactions:PartB
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• v.12B no.2 s.98
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• pp.123-130
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• 2005

In this paper, fingerprint identification algorithm using pixel direction factor in blocks is proposed to minimize false acceptance ratio and to apply security system. The proposed algorithm is that a fingerprint image is divided by 16 blocks, then feature parameters which have direct factors of $0^{\circ},\;45^{\circ},\;90^{\circ}\;and\;135^{\circ}$ is extracted for each block. Membership function of a reference fingerprint and an input fingerprint for the extracted parameters is calculated, then identification of two fingerprint is distinguished using fuzzy inference. False acceptance ratio is evaluated about different fingerprints of In kinds regardless of sex and shape which are obtained from adults, and false rejection ratio is evaluated about fingerprints which are obtained by adding fingerprints of 10 kinds on different fingerprints of 100 kinds. The experiment results is that false acceptance ratio is average $0.34\%$ about experiment of 4,950 times, and false rejection ratio is average $3.7\%$ about experiment of 1,000 times. The proposed algerian is excellent for recognition rate and security.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.1
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• pp.81-87
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• 2013

In this paper, we propose a music search algorithm for automotive infotainment system. The proposed method extracts fingerprints using the high peaks based on log-spectrum of the music signal, and the extracted music fingerprints store in cloud server applying a hash value. In the cloud server, the most similar music is retrieved by comparing the user's query music with the fingerprints stored in hash table of cloud server. To evaluate the performance of the proposed music search algorithm, we measure an accuracy of the retrieved results according to various length of the query music and measure a retrieval time according to the number of stored music database in hash table.

• Biomedical Science Letters
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• v.13 no.4
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• pp.369-374
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• 2007

A fingerprint is an impression of the friction ridges of all or any part of the finger. A friction ridge is a raised portion of the epidermis on the palmar (palm and fingers) or plantar (sole and toes) skin, consisting of one or more connected ridge units of friction ridge skin. There are two fundamental principles underlying the use of fingerprints as a means of identifying individuals - immutability and uniqueness. Friction ridges develop on the fetus in their definitive form before birth. Ridges are persistent throughout life except for permanent scarring. Ridge patterns and the details in small areas of friction ridges are unique and never repeated. Friction ridge patterns vary within limits, which allow for classification. We developed the high temperature-moisturizing method to obtained quality postmortem impressions from decomposing friction ridge skin. This technique is a simple procedure that uses boiling water to recondition the skin. This reconditioning process enhances detail present on the fingers and exposes ridge detail not visible to the naked eye. Therefore, we can recover the quality fingerprints, even from the worst decomposed bodies.

• Journal of Ginseng Research
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• v.41 no.3
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• pp.339-346
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• 2017

Background: In this study, we investigated how to convert the Panax ginseng DNA sequence code and chemical fingerprints into a two-dimensional code. In order to improve the compression efficiency, GATC2Bytes and digital merger compression algorithms are proposed. Methods: HPLC chemical fingerprint data of 10 groups of P. ginseng from Northeast China and the internal transcribed spacer 2 (ITS2) sequence code as the DNA sequence code were ready for conversion. In order to convert such data into a two-dimensional code, the following six steps were performed: First, the chemical fingerprint characteristic data sets were obtained through the inflection filtering algorithm. Second, precompression processing of such data sets is undertaken. Third, precompression processing was undertaken with the P. ginseng DNA (ITS2) sequence codes. Fourth, the precompressed chemical fingerprint data and the DNA (ITS2) sequence code were combined in accordance with the set data format. Such combined data can be compressed by Zlib, an open source data compression algorithm. Finally, the compressed data generated a two-dimensional code called a quick response code (QR code). Results: Through the abovementioned converting process, it can be found that the number of bytes needed for storing P. ginseng chemical fingerprints and its DNA (ITS2) sequence code can be greatly reduced. After GTCA2Bytes algorithm processing, the ITS2 compression rate reaches 75% and the chemical fingerprint compression rate exceeds 99.65% via filtration and digital merger compression algorithm processing. Therefore, the overall compression ratio even exceeds 99.36%. The capacity of the formed QR code is around 0.5k, which can easily and successfully be read and identified by any smartphone. Conclusion: P. ginseng chemical fingerprints and its DNA (ITS2) sequence code can form a QR code after data processing, and therefore the QR code can be a perfect carrier of the authenticity and quality of P. ginseng information. This study provides a theoretical basis for the development of a quality traceability system of traditional Chinese medicine based on a two-dimensional code.

• Analytical Science and Technology
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• v.21 no.3
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• pp.212-221
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• 2008

In order to investigate the information for effective detection and developing of latent fingerprints, we identified fatty acids composition of latent fingerprints on non-porous evidence surface and the chemical changes of latent fingerprint residue after print deposition during 7 months. Fingerprints from eight Korean male donors (aged 29-50 years) and one female donor (aged 36 years) were collected. All fingerprints were found to contain lauric acid (C12:0), myristic acid (C14:0), palmitic acid (C16:0), stearic acid (C18:0), elaidic acid (C18:1n9t), oleic acid (C18:1n9c), linoleic acid (C18:2n6c), arachidic acid (C20:0), linolenic acid (C18:3n3), erucic acid (C22:1n9) and docosadienoic acid (C22:2) and primarily palmitic acid (35.45-48.37%), oleic acid (14.84-28.49%), stearic acid (9.71-24.96%) and linoleic acid (7.68-18.8%) occupied 75% of total fatty acids. When the fingerprints were deposited at dark room for 7 months, total fatty acids components decreased about 12-25%. It can be explained that significant degradation of long-chain fatty acids such as elaidic acid (C18:1n9t), arachidic acid (C20:0), linolenic acid (C18:3n3), erucic acid (C22:1n9), and docosadienoic acid (C22:2) resulted in the generation of myristic acid (C14:0), myristoleic acid (C14:1) and pentadecanoic acid (C15:0).

• Journal of forensic and investigative science
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• v.2 no.1
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• pp.84-86
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• 2007

• International Journal of Control, Automation, and Systems
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• v.6 no.6
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• pp.794-799
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• 2008

This paper presents a user identification method at H.264 streaming using watermarking with fingerprints. The watermark can efficiently reduce the potential danger of forgery or alteration. Especially a biometric watermark has convenient, economical advantages. The fingerprint watermark can also improve reliability of verification using automated fingerprint identification systems. These algorithms, however, are not robust against common video compression. To overcome this problem, we analyze H.264 compression pattern and extract watermark after restoring damaged watermark using various filters. The proposed algorithm consists of enhancement of a fingerprint image, watermark insertion using discrete wavelet transform and extraction after restoring. The proposed algorithm can achieve robust watermark extraction against H.264 compressed videos.

• Electronics and Telecommunications Trends
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• v.35 no.1
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• pp.25-33
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• 2020

Just as it is possible to distinguish people by using physical features, such as fingerprints, irises, veins, and faces, and behavioral features, such as voice, gait, keyboard input pattern, and signatures, the an IoT device includes various features that cannot be replicated. For example, there are differences in the physical structure of the chip, differences in computation time of the devices or circuits, differences in residual data when the SDRAM is turned on and off, and minute differences in sensor sensing results. Because of these differences, Sensor data can be collected and analyzed, based on these differences, to identify features that can classify the sensors and define them as sensor-based device DNA technology. As Similar to the biometrics, such as human fingerprints and irises, can be authenticatedused for authentication, sensor-based device DNA can be used to authenticate sensors and generate cryptographic keys that can be used for security.

• Asian-Australasian Journal of Animal Sciences
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• v.12 no.1
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• pp.1-4
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• 1999

Beijing White Chickens laying larger eggs and smaller eggs were respectively used as parental individuals for mating to produce the F1 progeny and then the F1 progeny individuals mated to produce 125 individuals of the F2 progeny. Three bands associated with the egg weight performance were identified from DNA fingerprints of the 125 individuals generated with a bovine minisatellite probe BM6.5B. The simple linear correlation analysis showed that the coefficients of correlation between frequencies of the three bands (DB1, DB2 and DB3) and egg weights were -0.6, -0.6 and 0.9, respectively.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.901-904
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• 2000

A direct authentication from gray-scale image, instead of the conventional multi-step preprocessing, is proposed using Gabor filter-based features from the gray-scale fingerprint around core point. The core point is located as a reference point for the translation invariant matching. And its principal symmetry axis is detected for the rotation invariant matching from its neighboring region centered at the core point. And then fingerprint is divided into non-overlapping blocks with respect to the core point and features are directly extracted form the blocked gray level fingerprint using Gabor filter. The proposed fingerprint authentication is based on the Euclidean distance between the corresponding Gabor features of the input and the template fingerprints. Experiments are conducted on 300${\times}$300 fingerprints obtained from a CMOS sensor with 500 dpi resolution, and the proposed method could lower the False Reject Rate(FRR) to 18.2% under False Acceptance Rate(FAR) of 0%.